Zero-defect metal additive manufacturing for aerospace and industrial supply chains using AI closed-loop process optimisation

The Challenge

Metal additive manufacturing via laser powder bed fusion (LPBF) promises lighter, cheaper, faster-to-market parts for aerospace, automotive and medical supply chains — but the process is notoriously hard to get right. LPBF uses a laser to melt metal powder into solid objects and is susceptible to defects such as porosity, cracking and residual stresses driven by laser power, scan speed and powder bed temperature. Failed builds waste expensive material and machine time, and quality-assurance burdens hold AM back from certified production use.

The Solution

iAM-3DPO set out to create a novel, integrated, laser-based system capable of achieving zero distortion and defects during the build process. The system incorporates optical/thermal monitoring capability and cloud-based, AI-enabled, closed-loop process-optimisation technology that uses predictive thermal simulations and adaptable process parameters to enable first-time-right manufacturability. NquiringMinds provided the data analytics and machine-learning expertise on the consortium, delivering the AI analytical models and cloud-based data sharing and analytics that close the loop between in-process monitoring and process adaptation.

Outcomes

The project delivered a multi-disciplinary LPBF system combining optical/thermal monitoring, diagnostic data acquisition, AI analytical models and cloud-based data sharing and analytics. Work packages spanned monitoring-system development, data-acquisition integration, AI/data-interpretation algorithms, data-driven modularisation of AM data, and cloud-based AI analytics deployment — targeting cost reductions, higher material utilisation, improved quality assurance and shorter design/processing cycles for AM supply chains. TWI published a case study, “NquiringMinds and J4IC Join Forces on IAM-3DPO Project”, documenting the consortium and approach.